Testing of elements used in communication links

ABSTRACT

A receiver for a communications link includes a receiver module and a host receiver. These two components can be tested independently. In one embodiment, the receiver module is characterized with respect to noise and distortion. The noise performance can be determined by comparing input and output signals of the receiver module, to determine the relative noise of the receiver module. The distortion performance can be determined by comparing the distortion of input and output signals of the receiver module, using a reference host receiver that includes an equalizer. The host receiver can be tested by using a reference receiver module.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application is a continuation of U.S. patent application Ser. No.11/427,765, “Testing of Receivers with Separate Linear O/E Module andHost Used in Communication Links,” filed Jun. 29, 2006, which claimspriority under 35 U.S.C. §119(e) to each of the following U.S.Provisional Patent Applications: Ser. No. 60/695,926, “SFP+ LinearModule Receiver Specifications And Test Methodology,” filed Jun. 30,2005; and Ser. No. 60/747,398, “Method For Tradeoff Between LinearOptical Module Rx Distortion And Noise,” filed May 16, 2006. The subjectmatter of all of the foregoing are incorporated herein by reference intheir entirety.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates generally to the testing of elements, such asreceivers, used in communications links, for example fiber opticcommunications links. More specifically, in cases where an element, suchas receiver, includes a linear front-end and a separate back-end (host)that includes equalization, this invention relates to separate testingof the front-end and/or back-end.

2. Description of the Related Art

Optical fiber is widely used as a communications medium in high speeddigital networks, including local area networks (LANs), storage areanetworks (SANs), and wide area networks (WANs). There has been a trendin optical networking towards ever-increasing data rates. While 100 Mbpswas once considered extremely fast for enterprise networking, attentionhas recently shifted to 10 Gbps, 100 times faster. As used in thisapplication, 10 Gigabit (abbreviated as 10 G or 10 Gbps or 10 Gbit/s)systems are understood to include optical fiber communication systemsthat have data rates or line rates (i.e., bit rates including overhead)of approximately 10 Gigabits per second. This includes, for example, LRMand SFF-8431, a specification currently under development by the SFFCommittee that will document the SFP+ specifications for 10G Ethernetand other 10G systems. While 10G systems serve as convenient examplesfor the current invention, the current invention is not limited to 10Gsystems. Examples of other systems to which the current invention couldbe applied include Fibre Channel systems, which currently operate atspeeds from 1 Gbps to 10 Gbps, as specified by the Technical CommitteeT11, a committee of the InterNational Committee for InformationTechnology Standards (INCITS).

Regardless of the specific data rate, application or architecture,communications links (including optical fiber communications links)invariably include a transmitter, a channel and a receiver. In anoptical fiber communications link, the transmitter typically convertsthe digital data to be sent to an optical form suitable for transmissionover the channel (i.e., the optical fiber). The optical signal istransported from the transmitter to the receiver over the channel,possibly suffering channel impairments along the way, and the receiverthen recovers the digital data from the received optical signal.

Recent developments in 10G optical communications have included the useof Electronic Dispersion Compensation (EDC) in receivers to extendrange. For example, the IEEE 802.3aq standards committee is developing astandard (10GBASE-LRM or simply LRM) for 10G Ethernet over multi-modefiber over distances of up to 220 meters using EDC. This standard is ina draft state, currently documented in IEEE Draft P802.3aq/D4.0, Draftamendment to: IEEE Standard for Informationtechnology—Telecommunications and information exchange betweensystems—Local and metropolitan area networks—Specific requirements, Part3: Carrier Sense Multiple Access with Collision Detection (CSMA/CD)Access Method and Physical Layer Specifications, Amendment: PhysicalLayer and Management Parameters for 10 Gb/s Operation, Type 10GBASE-LRM,referred to herein as IEEE 802.3aq/D4.0 or LRM, and incorporated byreference. The use of EDC in the receiver allows communication overlonger distances and/or use of lower cost components. Some of the addedwaveform distortions can be corrected in the EDC receiver. However, anEDC receiver generally requires linear signaling between the dispersionmechanism (e.g., the fiber) and the equalizer that performs the EDCfunction.

Standards play an important role in networking and communications. Sincecomponents in the network may come from different vendors, standardsensure that different components will interoperate with each other andthat overall system performance metrics can be achieved even whencomponents are sourced from different vendors. For example, standardsfor receivers can be used to ensure that, when compliant transmittersare combined with a compliant channel and a compliant receiver, theoverall link will meet certain minimum performance levels. As a result,manufacturers of receivers typically will want to test their receiversfor compliance with the relevant standards as part of theirqualification or production processes.

In the context of approaches such as LRM, the receiver may be dividedinto a module that contains the O/E conversion (e.g., a photodetector)and a host for the module. For convenience, these will be referred to asthe receiver module and host receiver, respectively. If the EDCcapability resides in the host receiver, then the O/E receiver modulepreferably is linear. However, the O/E module and the host may come fromdifferent vendors. Alternately, a system integrator may purchase O/Emodules from a supplier for integration into its own host. Regardless ofhow it is assembled, in order for the overall receiver to be compliant,the O/E receiver module and corresponding host receiver together must becompliant. Current standards such as LRM may define a single standardfor the receiver as a whole, without allocating requirements between thereceiver module and the host receiver. In addition, EDC drives the needfor a linear O/E module but EDC is a relatively new proposal. Olderstandards may provide separate specifications for the O/E module andhost, but they typically are oriented towards hard-limited O/E modulesrather than linear ones. In hard-limited O/E modules, if the inputsignal is above a threshold (nominally set at the average value of thesignal), the output is at a logic one (high) level; whenever the signalis below the threshold, the output it at a logic zero (low) level.Hard-limited O/E modules are not linear.

Thus, there is a need for a receiver testing and compliance measurementtechnique for communications links, including, for example, 10G opticalfiber communications links, where the linear receiver module and thehost receiver (which includes EDC) can be tested and qualifiedindependently.

SUMMARY OF THE INVENTION

The present invention overcomes the limitations of the prior art byproviding separate tests for elements of a communication link, such asthe linear receiver module and the host receiver. In one embodiment, theelement, such as a receiver module, is characterized with respect tonoise and distortion. The noise performance can be determined byapplying a test signal to the element under test, such as a receivermodule under test, measuring the output waveform, and comparing thenoise in the output to the noise in the input. The increase in noise isa measure of the noise added by the element, such as the receivermodule. The noise measurements preferably do not use averaging (whichwould suppress noise effects) and preferably do use techniques thatavoid the inclusion of (deterministic) distortion, such as usinghistograms on portions of the waveform that are “flat” or by subtractingthe variance of the signal. In one embodiment, the noise metric isrelative noise added by the element, such as the receiver module,denoted RN_(M) where the subscript M refers to the element, such as thereceiver module. Generically, relative noise in this case is defined asthe reciprocal of Q factor, which is a measure of signal to noiseperformance. In an alternate embodiment, Q factor is used as the noisemetric.

The distortion performance can be determined by using a referencereceiver that includes an equalizer. In one embodiment, the distortionmetric is based on a waveform and dispersion penalty (WDP). WDP for asignal is defined as the difference (in dB) between a reference signalto noise ratio (SNR), and the equivalent SNR at the slicer input of areference decision feedback equalizer (DFE) host receiver for thesignal. WDP is a measure of distortion in the signal. The distortionperformance of the receiver module is characterized by a differentialwaveform and dispersion penalty (dWDP_(M)), which is the differencebetween the WDP of a test signal applied to the receiver module and theWDP of the resulting output from the receiver module. The distortionmeasurements (such as dWDP_(M)) preferably use averaging of thedeterministic signal/waveform in order to avoid the effects of noise.

In one approach, a test signal is applied to the element under dest,such as a receiver module under test, and both the incoming test signaland the output from the element are sampled using standard testequipment. The captured waveforms are processed through a softwaresimulation of the reference host receiver (which includes an equalizer)to yield estimates of the two WDP values. These in turn can be used tocalculate dWDP_(M) by their difference. The use of a standard softwaresimulation of the reference host receiver avoids the difficultiesinherent with a hardware receiver (although hardware references couldalso be used) and allows a more accurate and repeatable measurement.

The noise and distortion measurements can be combined in different waysto define a standard for the element, such as a receiver module. UsingRN_(M) and dWDP_(M) as an example, one standard may set a maximum levelfor RN_(M) and an independent maximum level for dWDP_(M). As anotherexample, the standard may define allowable tradeoffs between RN_(M) anddWDP_(M), where good performance of one parameter would allow relaxedperformance of the other and vice versa. In one approach, a contour ofconstant bit error rate (BER) may be defined in RN_(M)−dWDP_(M) space.Receiver modules that lie on this contour or have better performance arecompliant. In yet another approach, the definition of dWDP_(M) mayinclude the effects of noise in the receiver module. In this approach,while the standard may be defined only in terms of dWDP_(M), noiseperformance is also accounted for indirectly through the definition ofdWDP_(M). That is, defined in this way, dWDP_(M) is a hybrid metric ofdistortion and noise.

The host receiver is tested in effect by using a reference element, suchas a reference receiver module. If the standard specifies test signalsfor the element (i.e., at the input of the element), an intermediatetest signal can be generated by adding effects of the element. Theintermediate test signal can then be applied to test the host receiver.For example, if the standard puts maximum limits on the RN_(M) anddWDP_(M) of the element (for example, a receiver module), the testsignal (which may already contain certain impairments) can be furtherdegraded by these maximum amounts of noise and distortion. The resultingintermediate test signal can be applied to the host receiver. The BER(or other performance metric) of the host receiver might then be used todetermine whether the host receiver complies with the standard.

Other aspects of the invention include methods and devices correspondingto the techniques described above.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention has other advantages and features which will be morereadily apparent from the following detailed description of theinvention and the appended claims, when taken in conjunction with theaccompanying drawings, in which:

FIG. 1 is a block diagram of one implementation of a 10G optical fibercommunications link with equalization.

FIG. 2 is a block diagram of one implementation of an SFP+ transceivermodule and corresponding host.

FIG. 3 is a block diagram of an example communications link suitable foruse with the invention.

FIG. 4 is a block diagram of an example test system according to thecurrent invention.

FIG. 5 illustrates a noise and distortion model for determining thenoise and/or distortion performance of a receiver module.

FIG. 6 is a block diagram of an example WDP test system according to theinvention.

FIG. 7 is a block diagram of one model of a test system for determiningthe distortion performance of a receiver module.

FIG. 8 is block diagram of a feedforward filter with a tap to adjust aconstant offset.

FIG. 9 is a diagram illustrating an example tradeoff approach that couldbe taken by various standards to allow a wider range of performancebetween noise and distortion of the receiver module.

FIG. 10 is a block diagram of an example test system for testing a hostreceiver.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 1 shows a 10G optical fiber communications link 100 with ElectronicDispersion Compensation (EDC). The link 100 includes a transmitter 105coupled through optical fiber 110 (the channel) to a receiver 120. Atypical transmitter 105 may include a serializer, or parallel/serialconverter (P/S) 106 for receiving 10G data from a data source on aplurality of parallel lines and providing serial data to a 10G laserdriver 108 via a clock and data recovery unit 107. The driver 108 thendrives a 10G laser source 109, which launches the optical waveformcarrying the digital data on optical fiber 110.

On the receive side, a typical receiver 120 includes a 10G photodetector111 for receiving and detecting data from the optical fiber 110. Thedetected data is typically processed through a 10G transimpedanceamplifier (TIA) 112, an equalizer (which applies the EDC correction)113, and a 10G clock and data recovery unit 114. The components beforethe equalizer 113 preferably have an aggregate response that is linearin order to reduce degradation of the equalizer 113 performance. Therecovered data may then be placed on a parallel data interface through aserial/parallel converter (S/P) 115.

In many applications, the electronic and optical components at each endof the link are housed in a transceiver module. In some applications,these modules are fixed to a host circuit board, and in otherapplications they are “pluggable” modules that can be inserted into andremoved from a cage (or socket) that is fixed to the host circuit card.Multi-Source Agreements (MSAs) have been developed to achieve somedegree of interoperability between modules from different manufacturers.Example MSAs include XFP and SFP+, in which the 10 Gbps electrical I/Ointerface to the host is serial, and X2, XPAK, and XENPAK, in which the10 Gbps electrical interface to the host is parallelized down to fourlanes in each direction. In most current MSAs, the transceiver modulemay contain a fair number of components: parallel to serial converter,transmit CDR, laser driver and laser on the transmit side; andphotodetector, transimpedance amplifier, equalizer, receive CDR andserial to parallel converter on the receive side.

FIG. 2 shows a block diagram for a new MSA: SFP+ transceiver module 250.The SFP+ next-generation form factor promises to be smaller, burn lesspower, require fewer components and be less expensive. This is becausethe MSA dictates that fewer components are included in the transceivermodule 250 itself: typically a laser driver 108 and laser 109 in thetransmit path; and a photodetector 111, transimpedance amplifier 112 andmaybe some type of post-amplifier 117 in the receive path. These modulesare envisioned for systems in which other shared functions (such as P/Sand S/P conversions, EDC and CDR) reside on the host circuit board 260.Moving functions outside the transceiver module 250 reduces size, costand power consumption of the module.

In the context of MSAs such as SFP+, the receiver includes a portion ofthe transceiver module 250 and a portion of the host 260. Forconvenience, these portions will be referred to as the O/E receivermodule (or just receiver module) and the host receiver, respectively,although the terms receiver module and host receiver are not intended tobe limited to transceivers. The transceiver module 250 and host 260 maycome from different vendors. Alternately, a system integrator maypurchase transceiver modules 250 from a supplier. Therefore, it isdesirable to be able to test the linear receiver module and the hostreceiver for compliance separately.

FIG. 3 is a more general block diagram of a communications link 300suitable for use with the current invention. FIG. 3 shows aunidirectional link but most actual systems are bidrectional. The link300 includes a transmitter 305 coupled through a channel 310 to areceiver 320. The receiver 320 includes a receiver module 350 coupled toa host receiver 360. The overall system 300 may suffer from variousimpairments in transmitting data from the transmitter 305 to thereceiver 320. The host receiver 360 includes equalization 313 to correctfor impairments arising from the channel 310. Accordingly, the receivermodule 350 ideally is linear, for example a linear O/E converter. Thetransmitters 305, channels 310 and receivers 320 may be various types,depending on the end application. Microwave, RF, cable, and opticalfiber are some examples of different media for the channel 310.Different types of modulation may be used by the transmitter 305. Someexamples are on-off keying (most commonly NRZ), QAM, PSK, and OFDM.Similarly, the receiver 320 can also take the various formscorresponding to these different modulation formats. As describedpreviously, the receiver module 350 and host receiver 360 may beprovided independently. Accordingly, it is desirable to be able toindependently test the receiver module 350 and the host receiver 360 forcompliance with standards.

Described below is a specific example based on 10GBASE-LRM. Theinvention is not limited to this standard or this data speed. It canalso be used for other 10G systems and/or for non-10G systems (e.g., 8GFibre Channel, as will be documented in FC-PI-4). In this case, theideal receiver module 350 is a noiseless, distortionless, linear O/Econverter.

An ideal receiver module 350 will convert the incoming optical signalinto an electrical signal with no change to the optical signal'swaveshape or its signal-to-noise ratio (SNR). The output of the idealreceiver module 350 would be an electrical signal that bears a perfectlinear relationship to the incoming optical signal (e.g., outputelectrical voltage is a linear function of the input optical intensity),with no added noise. However, any real receiver module will cause someamount of distortion of the waveshape and will add noise to the signal.Examples of distortion include filtering and nonlinearities (any changein amplitude and/or phase of the signal spectrum, whether caused by alinear or nonlinear process). Thus, one way to characterize the qualityof a receiver module is to quantify its noise performance and itsdistortion performance.

FIG. 4 is a block diagram of a test system according to the currentinvention. The purpose of the test system is to test the receivermodule, for example for compliance with a specific standard. As shown inthe bottom diagram of FIG. 4, a tester 430 generates a test signal 440,which is applied to the receiver module under test 450. The test signal440 typically is based on a data test pattern (e.g., a test pattern of1's and 0's). Many standards currently specify test signals for thereceiver as a whole (i.e., receiver module plus host receiver) and thesereceiver test signals may be used as the test signal 440 for thereceiver module. The receiver module 450 produces an output 462, whichis measured by a signal measurement device 465, for example a samplingoscilloscope. The measured waveform 462 may be stored in some medium467, for subsequent retrieval and processing. Alternately, the measuredwaveform 462 could be used immediately to determine the noise ordistortion performance of the receiver module 450.

The test signal 440 may also be measured without the receiver module, asshown in the top diagram of FIG. 4, or otherwise processed and/orprovided in a form suitable as a “reference” test signal 442 to allowcomparison with the output waveform 462 produced by the receiver module.

For example, if the raw test signal 440 is optical and the receivermodule 450 converts the incoming optical signal to an electrical outputwaveform 462, then the corresponding “reference” test signal measured inthe top diagram could be an electrical version 442 of the optical testsignal 440 where the O/E converter 455 is linear. The actual form of the“reference” test signal 442 and the processing applied to the testsignal 440 to produce the “reference” test signal will vary depending onthe specific measurement being made. The ideal O/E converter 455 shownin FIG. 4 is merely as an example.

The reference test signal 442 and output waveform 462 can be measured atdifferent times. For example, the test signal 440 can be applied to thetop diagram of FIG. 4 at a different time than when it is applied to thebottom diagram. Alternately, the test signal 440 may be split into twosignals, one that produces the output waveform 462 and another thatproduces the reference test signal 442. These two signals 442 and 462could be measured at the same time, for example by a dual inputoscilloscope.

FIG. 5 illustrates a noise and distortion model for determining theperformance of the linear receiver module 450. In this example, the testsignal is on-off keyed, NRZ switching between 0 and 1. Beginning withthe noise performance, for the incoming signal, the 0 level has a meanoptical power of P0 with rms noise of σ_(P0), and the 1 level has a meanoptical power of P1 with rms noise of σ_(P1). Similarly, the outputelectrical signal has mean voltages levels of V0 and V1, and rms noiseof σ_(V0) and σ_(V1), respectively for 0 and 1. The optical modulationamplitude (OMA) and voltage modulation amplitude (VMA) can then bedefined as OMA=P1−P0 and VMA=V1−V0. The gain G of the linear receivermodule is given by G=VMA/OMA.

In the context of 10GBASE-LRM measurements, in some cases, for exampleat the end of an optical fiber with dispersion, the values of P1 and P0may not be well-defined. Accordingly, repeating low frequency squarewave patterns are often used for testing. A typical low frequency squarewave pattern might have eight contiguous 1's followed by eightcontiguous 0's, where the actual number of 1's and 0's must besufficiently long to allow the optical levels to settle to their steadystate values. These test patterns are commonly referred to as OMApatterns 425. VMA measurements generally are made in a similar mannerwith the same patterns.

The noise performance at the input and output of the receiver module 450can be defined by the Q factor (which is one measure of signal to noise)Q _(in)=(P1−P0)/2σ_(P)=OMA/2σ_(P)  (1)Q _(out)=(V1−V0)/2σ_(V)=VMA/2σ_(V)Here, σ_(P) is the RMS value of σ_(P1) and σ_(P0). That is,σ_(P)=((σ_(P1) ²+σ_(P0) ²)/2)^(1/2). Similarly σ_(V) is the RMS value ofσ_(V1) and σ_(V0). (Note that Eqn. 1 defines the Q factor slightlydifferently from the usage in Eqn. 68-2 of 802.3aq. 802.3aq uses thelinear average of σ_(P1) and σ_(P0) for σ_(P). The two definitions areequivalent when σ_(P1)=σ_(P0).) Now introduce the concept of relativenoise RN asRN _(x)=1/Q _(x).  (2)Applying this to the input and output signals yieldsRN _(out)=1/Q _(out)=2σ_(V)/VMA  (3)RN _(in)=1/Q _(in)=2σ_(P)/OMA

The objective is to determine the impairing effect that the receivermodule has on RN_(out). Let σ_(M0) and σ_(M1) be the noise introduced bythe receiver module at its output, for the 0 and 1 levels, respectively,and let σ_(M) be the RMS values of σ_(M1) and σ_(M0). Then, assumingthat the input noise and the receiver noise are statisticallyindependent(σ_(V))²=(G*σ _(P))²+4(σ_(M))²/(VMA)²  (4)Multiplying each term by 4/(VMA)², substituting with Eqns. 3 for σ_(V)and σ_(P), and simplifying yields(RN _(out))²=(RN _(in))²+4(σ_(M))²/(VMA)²  (5)The rightmost term is the impairment due to the noise added by thereceiver module. Define the relative noise added by the receiver moduleasRN _(M)=2σ_(M)/VMA  (6)Then, Eqn. 5 can be rearranged to yieldRN _(M)=sqrt{(RN _(out))₂−(RN _(in))²}  (7)If the test pattern 440 is essentially noiseless, then RN_(in)≈0 andEqn. 7 reduces toRN _(M) ≈RN _(out)=2σ_(V)/(VMA)  (8)

Eqn. 8 was developed under several simplifying assumptions but similarresults can be developed without making the simplifying assumptions. Thegeneral result is that the noise contribution of the receiver module(expressed as RN_(M) in this case) can be determined based onmeasurements of the output waveform 462, and possibly also measurements442 of the incoming test signal 440 (for example if the incomingwaveform is not relatively noiseless).

The receiver module 450 under test generates a corresponding outputelectrical signal 462, which is measured by a sampling oscilloscope 465.The output noise preferably is measured with the receiver module 450operating in its normal range. For example, if the receiver module hasautomatic gain control, the incoming OMA pattern 440 should be set sothat the receiver module 450 is operating in its intended range.Otherwise, the noise levels and bandwidth may not represent actualoperation. The optical test pattern 440 can also be measured beforepassing through the receiver module, preferably using an appropriateoptical head for O/E conversion (with a fourth-order Bessel-Thomsonresponse in the case of LRM).

In one approach, RN_(M) is determined based on a vertical histogram forthe output voltage level for 1, and on a separate histogram for 0. Boththe signal (Vx) and noise magnitudes (σ_(Vx)) are measured. In thisapproach, the histograms are located and set to avoid measuringvariations in the deterministic portion of the signal. Preferably, aflat and stable portion of the waveform is used.

Another option for measuring the noise magnitude is the following. Thevariance of the entire test signal (both 0's and 1's together) ismeasured. This includes the variances of both the signal (including anydeterministic distortions) and the noise. Secondly, the variance of theentire test signal with averaging turned on is measured. In this case,the variance includes the variance of only the signal (and deterministicdistortions) since the noise will be suppressed by the averaging. Thesquare root of the difference is calculated. The difference will be thevariance due to the noise, and the square root will provide the rmsvalue of the noise. This method for noise measurement assumes a singularnoise value that is independent of logic level (consistent with theabove derivation, when it is assumed that σ_(X1)=σ_(X0)).

As described above, the tester 430 preferably is essentially noiselessso that RN_(out)>>RN_(in). Such a source can be accomplished, forexample as defined in Figure 68-10 in 802.3aq with the Gaussian noisesource disabled or simply not used, as illustrated in Figure 68-13. Inthis case, Eqn. 8 can be used (assuming the other simplifications arecorrect). When it is not true that RN_(out)>>RN_(in), Eqn. 7 should beused.

Measurements that have instrumentation characteristics preferably arecalibrated and/or compensated so that error is not introduced into themeasurement. For example, a recommended approach for measuring theincoming optical test signal 440 includes measuring the measuringinstrument 465's dark noise with no light entering the input. Designatethe measured rms noise with no input as σ_(Pdark). Similarly, formeasurements of the output waveform 462, the oscilloscope 465'selectrical noise can be measured with the input(s) terminated by amatching impedance (typically 50 ohms). Designate the measured rms noisewith no input as σ_(VNoSignal). Then, the terms σ_(P) and σ_(V) usedabove can be replaced by sqrt{(σ_(P))²−(σ_(Pdark))²} andsqrt{(σ_(V))²−(σ_(VNoSignal))²}, respectively to compensate for theeffects of instrument noise.

Moving now to the measurement of distortion introduced by the receivermodule, FIG. 6 is a block diagram of a software test system according tothe invention. In FIG. 6, a software simulator 470 accesses the waveform462 captured from the output of the receiver module 450 under test. Inthis example, the waveform 462 was previously captured and stored inmedia 467, although that is not required. The simulator 470 is designedto simulate the equalizer of a reference host receiver 474. The software470 processes the waveform 462 to simulate propagation of the waveformthrough the reference host receiver 474. A distortion metric 476 for thewaveform is calculated based on the simulated propagation. The data testpattern 425 may be used as an input to the software simulator 470.

In one approach, a reference test signal 442, which represents the inputto the receiver module under test 450, is also applied to the softwaresimulator (in FIG. 6, replace output waveform 462 with input waveform442) to yield a distortion metric for the input waveform. Therelationship of the reference test signal 442 to the raw test signal 440may vary, depending on the standard being tested. The distortion metricfor the receiver module is determined by comparing the distortion metricfor the input waveform 442 and that for the output waveform 462. Thechange in distortion metric is attributable to the receiver module 450under test.

The following example describes a test methodology where the distortionmetric is based on the Waveform and Dispersion Penalty (WDP). WDP isbased on similar concepts as the TWDP metric developed for transmitters,but applied to other points in the communications link, including thereceiver module. For a further description of TWDP, see U.S. patentapplication Ser. No. 11/316,115, “Testing Of Transmitters ForCommunication Links By Software Simulation Of Reference Channel And/OrReference Receiver,” filed Dec. 21, 2005, which is incorporated hereinby reference. One difference from TWDP is that the internal dispersivestressor/channels in TWDP are removed and replaced with a no-dispersionidentity channel, as described in LRM's text for calibration of the TP3test signal in clause 68.6.9.3.

The WDP for a signal X is defined asWDP=SNR_(REF)−SNR_(X) (dBo)  (9)where SNR_(REF) is a reference signal to noise ratio (SNR), expressed inoptical dB (dBo), and SNR_(X) is the equivalent SNR in dBo for a signalX measured at the slicer input of the reference decision feedbackequalizer (DFE) receiver for the measured waveform after propagationthrough a reference host receiver. In this particular example, SNR_(REF)is the SNR that would be realized by an ideal matched filter receiver ifthe received waveform were an ideal rectangular NRZ waveform withamplitude OMA and the receiver had additive white Gaussian noise (AWGN)of spectral density N₀.

The distortion metric for the receiver module is given by theDifferential Waveform and Dispersion Penalty (dWDP)dWDP_(M)=WDP_(out)−WDP_(in) (dBo)  (10)where WDP_(out) is the WDP for the signal 462 output by the receivermodule 450 under test and WDP_(in) is the WDP for the signal 442. In thecase of LRM, the reference test signal 442 is produced by passing theraw test signal 440 through an O/E converter 455 with a predefinedspectral response (specifically, a 7.5 GHz 4^(th)-order Bessel-Thomsonin the case of LRM). Substituting Eqn. 9 into Eqn. 10 yieldsdWDP_(M)=SNR_(in)−SNR_(out) (dBo)  (11)where the two SNR values are the SNR measured at the slicer input of thereference host receiver for the input and output signals, respectively.

In one approach, in a preferred embodiment, the two SNR_(X) values (andhence also dWDP_(M)) is calculated by MATLAB code as illustrated in FIG.7. The simulator 570 shown in FIG. 7 is similar to that used in thecalculation of TWDP, but the internal dispersive channels in TWDP arereplaced with an identity channel. Thus, the equalizer 584 effectivelybecomes the entire reference host receiver. Simulators other than theone shown in FIG. 7 can also be used. For example, an electrical channelcan be added to the simulator to represent the reference host receiver'sFR4 and/or IC package. The electrical channel could be added before orafter the noise model 577.

In addition, various noise models 577 (e.g., different magnitudes and/orspectra) can be used to account for different effects and more than onenoise source could be used. Generally speaking, there are multiple noisesources in a communications link, for example at the transmitter, fiber,receiver module and host receiver. The SNR at the slicer is affected byall of these noise sources, and the noise generated by these sourceswill pass through to the slicer with some magnitude and spectrum. All ofthese noise sources should be accounted for in order to get the mostaccurate result for WDP, and one approach is to use a noise model 577that accounts for these different sources. In order to locate all thenoise sources into one location in the host receiver model (577) in themost accurate manner, the effects of upstream filtering and gains/lossesfor each noise source should be accounted for in determining theaggregate noise power spectral density.

However, there typically is a tradeoff between accuracy and simplicity.More accurate models may introduce unwanted complexity. For example, inan alternate approach, the noise model 577 could be a single white noisesource. This simplifies the model 577 and accuracy sufficient fortesting could be retained in a number of ways. For example, the whitenoise source could be selected to have the same characteristics (withrespect to the test) as the aggregate of the underlying noise sources.For example, the white noise source could be selected to have the sameoverall noise power or the same low frequency noise power density.Alternately, the white noise source could be selected to produce moreconservative results than the aggregate underlying noise sources.

Waveform 552 (which is either the input signal 442 or output signal 462,depending on which SNR is being calculated) is digitized and captured563. The oscilloscope is set to capture at least one complete cycle ofthe periodic signal 550 with at least seven samples per unit interval.The number of samples per unit interval is not critical as long as thesampling rate is high enough to capture the high frequency content ofthe signal without aliasing.

The inputs to the software simulator 570 include the following:

-   -   The captured waveform 568, which, in this specific example, is        one complete cycle of the digitized waveform 566 with an integer        number of samples per bit period or unit interval—e.g., one        complete cycle of the waveform resulting from a periodic test        signal. In some cases, the digitized waveform 566 is        pre-processed (e.g., re-sampled, truncated and/or aligned with        the underlying data test pattern, as necessary) to produce the        captured waveform 568. In other cases, pre-processing may not be        necessary and the digitized waveform 566 can be used directly as        the captured waveform 568. In a preferred embodiment, the        captured waveform 568 has 16 samples per unit interval. The        number of samples per unit interval is not critical as long as        the sampling rate is high enough to represent the high frequency        content of the signal without aliasing.    -   One complete cycle of the test data pattern 542 used to generate        the captured waveform 568. The test data pattern 542 and the        captured waveform 568 are aligned (i.e., a rectangular pulse        train based on the test data pattern 542 is aligned in time with        the captured waveform 568 within one unit interval). The test        data pattern 542 has period N (e.g., 511 for PRBS9) and one        cycle is denoted {x(n)}, where 0≦n≦N−1.        The preprocessing steps of re-sampling, truncation to one        complete cycle, and alignment with the test data pattern are        shown performed in block 567 outside the simulator 570 and        outside the sampling oscilloscope 565. Alternatively, some or        all of these steps may be performed as part of the simulator        570, or inside the sampling oscilloscope 565, or as part of the        digitization and capture 563.

In a preferred embodiment, the captured waveform 568 is processed by thesoftware simulator 570, as follows:

1. The captured waveform 568 is normalized 571. The OMA (for inputsignal 442 or VMA for output signal 462) and baseline (steady state zerolevel) of the waveform 568 are either measured separately and entered asinputs to the algorithm, or alternatively they are estimated from thecaptured waveform. The zero-level (baseline) is subtracted from thewaveform 568 and the waveform is scaled such that the resulting OMA (orVMA) is 1. Thus, the normalized waveform has a baseline of 0 and an OMA(or VMA) of 1. In the LRM case, N₀ is set such that SNR_(REF) of Eqn. 9is 14.97 dBo.

2. The normalized waveform plus noise 577 is passed through anantialiasing filter 573. A fourth-order Butterworth filter of bandwidth7.5 GHz is used in this example. An alternative embodiment would omitthe antialiasing filter 573 but would instead filter the Gaussian noise577 before adding it to the receiver module output 576.

3. The output signal from the antialiasing filter 573 is sampled 574 atrate 2/T with sampling phase φ. An alternate embodiment using a matchedfilter and a rate 1/T sampler is described below. The sampler output 575is denoted y_(φ)(nT/2), which has a deterministic component and a randomcomponent given byy _(φ)(nT/2)=r(n)+η(n).The sequence {r(n)} is the deterministic sampled version of the filteredoutput of the receiver module; it is periodic with period 2N. Thesequence {η(n)} is a discrete-time noise sequence which is obtained bypassing the AWGN through the anti-aliasing filter and sampling.

4. The sampled signal is processed by a fractionally-spaced MMSE-DFEreceiver 584 with N_(f) feedforward taps (at T/2 spacing) 585 and N_(b)feedback taps 586. For example, N_(f) can be set to 14 and N_(b) can beset to 5. The use of 14 feedforward taps and 5 feedback taps are examplesettings; the number of taps can be different depending on the desiredcapabilities of the reference DFE receiver. The feedforward filter isoptionally augmented with an extra (N_(f)+1^(th)) tap that adjusts tooptimize a constant offset, as shown in FIG. 8 and described more fullybelow. The feedforward and feedback tap coefficients are calculatedusing a least-squares approach that minimizes the mean-squared error atthe slicer 578 input for the given captured waveform, assuming the noisepower spectral density N₀ is set as described above.

FIG. 7 shows the channel and equalizer model used for the least-squarescalculation. The reference DFE consists of a feedforward filter {W(0), .. . , W(N_(f)−1)}, an optional constant offset coefficient W(N_(f)) (asshown in FIG. 8), and a feedback filter {B(1), . . . , B(N_(b))}. Aconventional DFE would feedback decisions {{circumflex over (x)}(n)}. Inthis case, the decisions are assumed to be correct and the decided bitsare therefore replaced with the transmitted bits {x(n)}. While a finitelength equalizer is shown in this example, an alternate embodiment wouldinclude an infinite length equalizer, performance of which could becomputed analytically.

The feedback filter 586 is symbol spaced and strictly causal, feedingback the N_(b) bits prior to the current bit x(n). The input sequence onwhich the slicer makes decisions is denoted {z(n)}, where

$\begin{matrix}\begin{matrix}{{z(n)} = {{\sum\limits_{k = 0}^{N_{f} - 1}{{W(k)}{y_{\phi}( {{nT} + {DT} - {{kT}/2}} )}}} +}} \\{{W( N_{f} )} - {\sum\limits_{k = 1}^{N_{b}}{{B(k)}{x( {n - k} )}}}} \\{= {{\sum\limits_{k = 0}^{N_{f} - 1}{{W(k)}( {{r( {{2n} + {2D} - k} )} + {\eta( {{2n} + {2D} - k} )}} )}} +}} \\{{W( N_{f} )} - {\sum\limits_{k = 1}^{N_{b}}{{B(k)}{x( {n - k} )}}}}\end{matrix} & (12)\end{matrix}$Eqn. 12 includes the term W(N_(f)), which is the optional constantoffset coefficient for automated offset compensation; without offsetcompensation, W(N_(f)) would be absent (or set to 0). In Eqn. 12, D isan integer such that the number of anticausal T/2-spaced taps in thefeedforward filter is 2D. While the feedforward filter is modeled ashaving anticausal taps, a practical equalizer would delay decisions byDT so that the overall system is causal. DT is referred to as theequalizer delay. Sometimes the equalizer delay is expressed as thenumber of feedforward anticausal taps, 2D.

The least-squares solution for the feedforward and feedback filtersminimizes the quantity

${MSE} = {E\lbrack {\sum\limits_{n = 0}^{N - 1}( {{z(n)} - {x(n)}} )^{2}} \rbrack}$where the expectation operator, E, refers to the random noise at theslicer input, which results from the additive Gaussian noise 577,filtered through the antialiasing filter 573, sampled 574, and filteredby the feedforward filter 585. (Here MSE is actually N times themean-squared error when averaged over the input sequence {x(n)}.) Thealgorithm finds the optimal W vector, B vector, and equalizer delay DTsuch that the mean-squared error is minimized in an efficient manner,for example as described in P. A. Voois, I. Lee, and J. M. Cioffi, “Theeffect of decision delay in finite-length decision feedbackequalization,” IEEE Transactions on Information Theory, vol. 53, pp.618-621, March 1996, which is incorporated herein by reference. Theoptimal sampling phase φ for the T/2 sampler is found by a brute-forcesearch over the 16 sampling phases in the unit interval. Note that for asufficiently long equalizer, that is, for N_(f) and N_(b) sufficientlylarge, the MSE is insensitive to sampling phase and equalizer delay. Inthat case, the number of anticausal taps 2D can be set to N_(f)/2, forexample, and optimization over D and φ can be omitted. Further detailsof the mean squared error (MSE) minimization are given below.

5. Once the MSE is minimized by finding the optimal sampling phase,equalizer delay, and tap coefficients, the bit-error rate is calculatedby the semi-analytic method. In an actual receiver, the slicer wouldmake binary decisions on its input based on whether the input is greaterthan or less than the slicer threshold. The probability of making anerror depends on the amplitude of the input signal, the statistics ofthe input noise, and the threshold of the slicer, which for this exampleis set to ½. The overall bit-error rate is calculated as follows:

-   -   a. The Gaussian noise variance at the input to the slicer 578 is        calculated.    -   b. For each bit in the data test pattern, the equalized input        signal to the slicer 578 is calculated and the probability of        error calculated based on the amplitude of the input signal, the        variance of the input noise, and the threshold value.    -   c. The probabilities of error are averaged over all bits in the        data test pattern to compute a total probability of error        BER_(X).

6. The equivalent SNR in optical dB is derived from the BER_(X)according toSNR_(N)=10 log₁₀₍ Q ⁻¹(BER_(X))) (dBo)  (13)

7. The dWDP_(M) for the receiver module under test is equal to thedifference (in optical dB) between WDP_(out) and WDP_(in), which can beequivalently calculated as the difference between SNR_(in) and SNR_(out)as shown in Eqn. 11 above.

There are additional alternate embodiments that are related to theexample algorithm described above. For example, the algorithm describedabove minimizes MSE at the slicer input, since that is how mostpractical equalizers are implemented. Alternatively, the referencereceiver could minimize bit error rate (BER) or some other performancemetric to compute the receiver module penalty. Minimization of BER wouldnot necessarily result in the same penalty as that computed byminimizing mean squared error.

Automated offset optimization is now discussed in additional detail. Inone embodiment, the WDP algorithm corrects for inaccuracies in theestimated value of the baseline (or steady state zero level). Thisautomated offset method makes the reported WDP (or SNR) valueindependent of estimation error in the baseline. In fact, it obviatesthe need to measure a baseline at all provided the ratio of baselinevalue to OMA is not unreasonably large. After OMA normalization andsubtraction of the estimated baseline, the resulting normalized waveformhas target signal values of “0” and “1”. The slicer threshold for BERdetermination is set at ½. An error in baseline estimation such that theresulting waveform is improperly offset and not centered about ½ willresult in a higher BER than if the offset were optimized. This offsetoptimization can be alternatively viewed as a threshold optimization.

The automated offset optimization can be accomplished by extending thevector of feedforward equalizer tap coefficients by 1. The additionaltap is not fed by a delayed version of the received signal, but isinstead fed by the constant 1. FIG. 8 shows an example feedforwardfilter with N_(f) regular taps and an extra (N_(f)+1)^(th) tap foroffset optimization. The MMSE tap coefficients are then calculated inthe normal fashion, and the coefficient of the extra tap essentiallygives the offset that minimizes mean squared error with the targetsignal values. While this method has been described as adjustment of anextra tap in the FFE to minimize MSE, other methods could be used to addan offset constant, the value of which is optimized in some sense. Forexample, one alternate method extends the length of the feedback tapcoefficient vector by one, feeding that extra feedback tap by theconstant 1, and computing the offset as part of the feedback tapcoefficient vector.

FIGS. 4-8 illustrated several examples for quantifying the noiseperformance and the distortion performance of a receiver module, usingthe quantities of relative noise RN_(M) and Differential Waveform andDispersion Penalty dWDP_(M) for the 10GBASE-LRM standard as an example.These measurements can be used to determine compliance with standards ina number of ways.

In one approach, a standard can set a separate limit for RN and fordWDP. In one example shown in FIG. 9, boundary 910 defines the standard.The standard requires that RN_(M)<0.033 and dWDP_(M)<0.5 dB. The area ofcompliance is the rectangular area 912. In an alternate approach, thecurve 920 defines the standard. The region 922 on the origin-side ofcurve 920 is the compliance region. Receiver modules that fall withinthis area 922 are in compliance. The border 920 could be defined as acontour of constant BER. In other words, all points along the curve 920would have the same BER. That BER could be achieved by lower distortionand higher noise, higher distortion and lower noise, or some tradeoff ofthe two. The area inside the curve (i.e., towards the origin) representslower BER.

In another approach, refer again to FIG. 7. In this model forcalculating dWDP, the noise source 577 is a reference white noise anddoes not take into account the actual noise of the receiver module. Inother words, the noise 577 used to calculate SNR_(X) (or, equivalentlyWDP_(X)) is the same noise as is used to calculate RN_(X). Thus,dWDP_(M) calculated in this manner is largely independent of the actualnoise in the receiver module.

In an alternate approach, actual noise measurements are used tocalculate WDP_(out) in FIG. 7 (and then dWDP_(M)). For example, whencalculating WDP_(out), the noise model 577 may be supplemented orreplaced by actual noise measurements. When calculated in this manner,dWDP_(M) is a function of the noise in the receiver module and is ahybrid measure of both distortion and noise, rather than primarily justdistortion. The standard could be defined with respect to just this onehybrid quantity, for example requiring dWDP_(M) measured in this way tofall below a maximum. Alternately, the standard could be defined withrespect to this hybrid dWDP_(M) in addition to other measures ofdistortion and/or noise.

As another example, the dWDP algorithm described above uses a testsignal 540 that includes various effects from a single optical fiberreference channel. Alternatively, a number of different effects and/oroptical fiber reference channels may be simulated by using a set of testsignals 540. A dWDP is calculated for each test signal. Receiver modulecompliance can be defined in terms of the collection of dWDP values. Forexample, compliance can require that a certain percentage of the dWDPvalues be below some threshold (or meet the specific requirements of thestandard). In particular, all of the dWDP values could be required to bebelow some limit. Alternately, different requirements could be definedfor different reference channels or classes of reference channels. Itwill be readily apparent that many different compliance criteria can bedefined, all of which should be considered within the scope of thisinvention.

The actual quantitative limits for RN and/or dWDP (or other measurementsof receiver module noise and/or distortion) will depend on the specificapplication and standard. The following is one example approach fordetermining appropriate quantitative limits for LRM.

Beginning with RN, during the development of fiber optic standards, anoptical power budget is typically developed. The budget generallyconsiders transmit powers, receiver sensitivity, DC losses due to fibersand connectors, AC penalties due to dispersion and noises, and possiblysome margin. The terms in the budget produce a target Q factor (peak torms SNR) at the slicer input of the receiver that is sufficient toattain a required BER. With signal-independent additive Gaussian noiseassumptions, for example, the target Q factor, Q_(sens), is 8.47 dBoptical to attain BER=1E-12.

Receiver sensitivity is a measure of receiver noise and is usuallydefined in terms of signal strength of a perfect (no noise and nodistortion) NRZ input signal with which the target Q factor must beachieved. The signal is commonly expressed in units of dBm, OMA,although other units are possible. For example, LRM has budgeted apractical receiver sensitivity of ˜12.6 dBm, OMA. Standards bodiestypically assume that the noise magnitude that corresponds to receiversensitivity is independent of the input signal level.

In LRM, −6.5 dBm is the minimum OMA expected in an actual applicationand sets the minimum OMA used for receiver testing. The minimum OMA is(−6.5−−12.6)=6.1 dB greater than the budgeted receiver sensitivityvalue. With these assumptions for test OMA and sensitivity, and stillassuming a perfect input test signal with no noise, it is expected thatQ _(minOMA) =Q _(sens)+6.1=14.57 dB (optical).Further, assume that the rest of the receiver is perfect and that thenoise limitation on sensitivity occurs entirely within the receivermodule. With the same assumptions, the Q factor at the receiver moduleoutput would beQ _(M) =Q _(minOMA)=14.57 dB.Since RN_(M)=1/Q_(M), thenRN _(M)=−14.57 dB=0.035  (14)

This is the value imposed on the module receiver to just meet the targetQ factor requirements of the LRM budget. Name this RN_(target). Anyvalue of RN_(M) that is lower than this value would increase SNR andwould be considered compliant. That is, in one approach, the standardcould requireRN_(M)<RN_(target)  (15)where RN_(M) is RN for the receiver module under test andRN_(target)=0.035.

In practice, the rest of the receiver is not perfect. Therefore, themodule must perform better than RN_(target) so that the entire receivermeets the requirement of RN_(target). For example, in FIG. 9, themaximum RN_(M) is set at 0.033. Further, RN_(target) target may bedependent on the module's dWDP in a tradeoff scenario.

Turning now to distortion, in the standards budgeting process,assumptions about the performance of the receiver are made. In the caseof equalizing receivers, a configuration and performance such as numberof taps, resolution, and other attributes may be assumed. This receiveris referred to as a reference receiver. If an actual receiver has thesame properties as the reference receiver, and the input signal containsthe same signal strength, noise, and penalty characteristics as thoseassumed during the budgeting process, then the link should result in thesame SNR or BER level as in the budget.

However, unlike noise performance (e.g., RN_(M)), no exact quantitativerule currently exists for setting distortion limits (e.g., dWDP_(M)) forthe receiver module. Often, distortion performance and the correspondingcosts can be traded off between the receiver module and the hostreceiver.

Assume that the budget has margin M (in dB) for the overall system. Insome cases, for example LRM, a portion M_(Rx) of the overall margin isallocated to the receiver to allow for implementation penalties, wherethe reference receiver that is assumed is better than ones expected inpractice. With this approach, the actual receiver is allowed up toM_(Rx) dB worse performance than the reference receiver while stillsupporting Q_(sens) at the slicer input.

Some of M_(Rx) may be allocated to the receiver module dWDP_(M). Forexample, if M_(Rx)=2.5 dB for the receiver, 0.5 dB might be allowed fordWDP_(M). This would leave 2.0 dB for other receiver implementationpenalties, M_(RxOther). 0.5 dB is merely an example. Other values may bechosen depending on receiver module and host receiver tradeoffs. Thereceiver module has consumed some of M_(Rx), and so the performance ofthe host receiver must be accordingly better in order to meet theoverall receiver margin M_(Rx). This is verified in testing by applyinga more stressful test signal to the host receiver that includes thedistortion added by the receiver module, while requiring that the hostreceiver still meet its SNR or BER specifications.

It is possible to allow more to dWDP_(M) if the specifications for thereceiver module recognize that the module's sensitivity (RN_(M)performance) could be better than budgeting expectations. In thissituation, it is possible that the penalty as seen at the slicer inputdue to a larger dWDP_(M) can be offset by lower RN_(M), thus preservingmore margin for M_(RxOther). Likewise, a lower dWDP_(M) could allow ahigher value for RN_(M), etc.

In other cases, it may be expected that actual receivers perform betterthan the reference receiver. In this case, there is usually no marginallocated in the original budget or for receiver implementation. Thatis, budget for actual receivers may already exist for dWDP_(M), eventhough not explicitly allocated. This case can be tested by applying amore stressful test signal to the host receiver that includes thedistortion added by the receiver module, while requiring that the hostreceiver still meet its SNR or BER specifications. This effectivelyforces that the host receiver has a better receiver than assumed for thehost's reference receiver in the budget.

Turning now to testing of the host receiver, FIG. 10 is a block diagramof a test system for testing a host receiver. Current standards mayspecify a test signal to be applied to the input of a receiver (i.e.,the input to the receiver module) and a required performance at theoutput of the receiver (i.e., the output of the host receiver). However,the system in FIG. 10 is intended to test just the host receiver withouta specific receiver module.

This is accomplished in effect by using a reference receiver module1050. For example, if the standard specifies a receiver test signal1040, then the tester 1030 generates this test signal 1040 and thereference receiver module 1050 adds noise and distortion. The resultingintermediate test signal 1055 is then applied to the host receiver undertest 1060. The performance of the host receiver 1060 is compared to thestandard to determine whether the host receiver 1060 complies. FIG. 10shows the reference receiver module 1050 as a separate box. This is doneto illustrate the net effect but the actual implementation may achievethe same effect without a separate reference receiver module 1050. Thatis, test equipment may directly generate the intermediate test signal1055 with similar characteristics to that which would be produced by areference receiver when fed by the receiver test signal 1040; an actualphysical realization of the reference receiver module 1050 may not beimplemented in practice.

For example, to continue the LRM example from above, assume that thestandard for the receiver module was defined by boundary 910 in FIG. 9.That is, RN_(M)<0.033 and dWDP_(M)<0.5 dB in order for the receivermodule to be compliant. Then one approach to testing the host receiver1060 is to add the maximum allowable module noise and module distortion(i.e., RN_(M) of 0.033 and dWDP_(M) of 0.5 dB) to a test signal 1040specified for the overall receiver. The VMA range preferably would beset over the range allowed by the standard or expected in the field. Theresulting signal 1055 is then used as the input test signal for the hostreceiver 1160. Usually, the standard may define a maximum BER at theoutput of the host receiver 1160.

As another example, if the standard was defined by boundary 920 in FIG.9, the host receiver 1060 could be tested by applying differentcombinations of RN_(M) and dWDP_(M) to the receiver test signal 1040,thus testing the host receiver at different points along the boundary920.

The detailed description above provides methods for testing hostreceivers and receiver modules that may be supplied by differentmanufacturers. It is possible that these methods could form the basis ofa standard that defines compliance criteria to ensure interoperability.Simplified tests may be derived for use in production when the resultsof such tests are well correlated with the results of the testsdescribed here. For example, a limit on dWDP may correlate well with alimit on the total harmonic distortion introduced by a module, and asimplified total harmonic distortion test might be used in production toreduce test time. The scope of the current invention is intended tocover such methods when the underlying compliance criteria are based ofthe methods described herein.

Although the detailed description contains many specifics, these shouldnot be construed as limiting the scope of the invention but merely asillustrating different examples and aspects of the invention. It shouldbe appreciated that the scope of the invention includes otherembodiments not discussed in detail above. Various other modifications,changes and variations which will be apparent to those skilled in theart may be made in the arrangement, operation and details of the methodand apparatus of the present invention disclosed herein withoutdeparting from the spirit and scope of the invention as defined in theappended claims. Therefore, the scope of the invention should bedetermined by the appended claims and their legal equivalents.

What is claimed is:
 1. A method for testing an element of acommunication link intended for use with a receiver that includesequalization, the method comprising: measuring an output waveform forthe element under test using a signal measurement device, wherein theoutput waveform is generated by the element in response to a test signalapplied to the element under test; processing the output waveform insoftware executed by a simulator, to simulate propagation of the outputwaveform through a reference receiver that includes an equalizer;calculating a distortion metric for the element based on the simulatedpropagated output waveform; and determining a noise performance of theelement.
 2. The method of claim 1, wherein the communications linkcomprises a microwave channel.
 3. The method of claim 1, wherein thecommunications link comprises a radio frequency channel.
 4. The methodof claim 1, wherein the communications link comprises a cable channel.5. The method of claim 1, wherein the equalizer includes a decisionfeedback equalizer comprising a feedforward filter and a feedbackfilter.
 6. The method of claim 5 wherein the feedforward filter is afractionally spaced feedforward filter.
 7. The method of claim 5 whereinthe feedforward filter includes a tap fed by a constant.
 8. The methodof claim 1, wherein the equalizer comprises a feedforward equalizerincluding a feedforward filter.
 9. The method of claim 8, wherein thefeedforward filter is a fractionally spaced feedforward filter.
 10. Themethod of claim 8, wherein the feedforward filter includes a tap fed bya constant.
 11. The method of claim 1, wherein the equalizer includes adecision feedback equalizer comprising a feedback filter.
 12. The methodof claim 1, further comprising: measuring an input waveform for theelement under test, wherein the input waveform is based on the testsignal applied to the element under test; processing the input waveformin software, to simulate propagation of the input waveform through thereference receiver; and wherein the step of calculating the distortionmetric for the element is further based on the simulated propagatedinput waveform.
 13. The method of claim 12, wherein the distortionmetric is a difference between (a) SNR for the simulated propagatedinput waveform and (b) SNR for the simulated propagated output waveform.14. The method of claim 13, wherein the reference receiver includes anequalizer with a slicer, and the SNR for the simulated propagated inputwaveform and the SNR for the simulated propagated output waveform aremeasured at an input to the slicer.
 15. The method of claim 12, furthercomprising splitting the test signal into two test signals, wherein oneof the test signals is used to produce the input waveform and the othertest signal is applied to the element under test to produce the outputwaveform.
 16. The method of claim 1 wherein the distortion metric isbased on compliance with a standard describing a maximum amount ofrelative noise added by the element and a maximum amount of differentialwaveform and dispersion penalty associated with the element.
 17. Themethod of claim 1 wherein the distortion metric is based on compliancewith a standard describing a maximum amount of relative noise added bythe element or a maximum differential waveform and dispersion penaltyassociated with the element.
 18. The method of claim 1 wherein: theequalizer includes a decision feedback equalizer having a feedforwardfilter and a feedback filter and a slicer; the step of calculating thedistortion metric for the element further comprises: measuring an inputwaveform for the element under test, wherein the input waveform is basedon the test signal applied to the element; processing the input waveformin software, to simulate propagation of the input waveform through thereference receiver; and wherein the step of calculating the distortionmetric for the element is further based on the simulated propagatedinput waveform; and the distortion metric is a difference between (a)SNR for the simulated propagated input waveform and (b) SNR for thesimulated propagated output waveform, and the SNR for the simulatedpropagated input waveform and the SNR for the simulated propagatedoutput waveform are measured at an input to the slicer.
 19. The methodof claim 1 wherein: the equalizer includes a decision feedback equalizerhaving a feedback filter and a slicer; the step of calculating thedistortion metric for the element further comprises: measuring an inputwaveform for the element under test, wherein the input waveform is basedon the test signal applied to the element; processing the input waveformin software, to simulate propagation of the input waveform through thereference receiver; and wherein the step of calculating the distortionmetric for the element is further based on the simulated propagatedinput waveform; and the distortion metric is a difference between (a)SNR for the simulated propagated input waveform and (b) SNR for thesimulated propagated output waveform, and the SNR for the simulatedpropagated input waveform and the SNR for the simulated propagatedoutput waveform are measured at an input to the slicer.
 20. The methodof claim 1 wherein: the equalizer includes a feedforward equalizerhaving a feedforward filter and a slicer; the step of calculating thedistortion metric for the element further comprises: measuring an inputwaveform for the element under test, wherein the input waveform is basedon the test signal applied to the element; processing the input waveformin software, to simulate propagation of the input waveform through thereference receiver; and wherein the step of calculating the distortionmetric for the element is further based on the simulated propagatedinput waveform; and the distortion metric is a difference between (a)SNR for the simulated propagated input waveform and (b) SNR for thesimulated propagated output waveform, and the SNR for the simulatedpropagated input waveform and the SNR for the simulated propagatedoutput waveform are measured at an input to the slicer.
 21. The methodof claim 1 wherein the distortion metric includes dWDP.
 22. The methodof claim 21 wherein the noise metric includes RN.
 23. The method ofclaim 1 wherein the step of determining a noise performance of theelement comprises: measuring noise at an input of the element; measuringnoise at an output of the element; and determining a noise performancebased on the measured noise at the input and at the output of theelement.
 24. The method of claim 1 further comprising the step of:determining compliance with a standard specifying a minimum performancelevel of the element by comparing the distortion metric and the noiseperformance to one or more quantitative limits in the standard.
 25. Themethod of claim 24, wherein the one or more quantitative limits in thestandard set a maximum on a distortion metric and also set a maximum ona noise metric.
 26. The method of claim 24, wherein the one or morequantitative limits in the standard define combinations of a distortionmetric and a noise metric that are compliant.
 27. The method of claim 26wherein the standard is defined by a contour of constant bit error ratefor the receiver.
 28. The method of claim 24, wherein the one or morequantitative limits in standard set a maximum on a distortion metric,and the distortion metric is a function of the noise performance.
 29. Atest system for testing an element of a communication link intended foruse with a receiver for the communications link, the test systemcomprising a software simulator for: receiving an output waveform forthe element under test, wherein the output waveform is based on anelectrical output generated by the element in response to a test signalapplied to the element; processing the output waveform in software, tosimulate propagation of the output waveform through a reference receiverthat includes an equalizer; and calculating a distortion metric for theelement based on the simulated propagated output waveform.
 30. Thesystem of claim 29, wherein the equalizer includes a decision feedbackequalizer comprising a feedforward filter and a feedback filter.
 31. Thesystem of claim 29, wherein the feedforward filter is a fractionallyspaced feedforward filter.
 32. The system of claim 29, wherein thefeedforward filter includes a tap fed by a constant.
 33. The system ofclaim 29, wherein the equalizer comprises a feedforward equalizerincluding a feedforward filter.
 34. The system of claim 33, wherein thefeedforward filter is a fractionally spaced feedforward filter.
 35. Thesystem of claim 33, wherein the feedforward filter includes a tap fed bya constant.
 36. The system of claim 29, wherein the equalizer includes adecision feedback equalizer comprising a feedback filter.
 37. The systemof claim 29, wherein calculating the distortion metric for the elementbased on the simulated propagated output waveform comprises: measuringan input waveform for the element under test, wherein the input waveformis based on the test signal applied to the element; processing the inputwaveform in software, to simulate propagation of the input waveformthrough the reference receiver; and calculating the distortion metricfor the element based on the simulated propagated output waveform andthe simulated propagated input waveform.
 38. The system of claim 37,wherein the distortion metric is a difference between (a) a SNR for thesimulated propagated input waveform and (b) SNR for the simulatedpropagated output waveform.
 39. The system of claim 38, wherein thereference receiver includes an equalizer with a slicer, and the SNR forthe simulated propagated input waveform and the SNR for the simulatedpropagated output waveform are measured at an input to the slicer. 40.The system of claim 37, wherein: the input waveform and the outputwaveform are produced by splitting the test signal into two testsignals, wherein one of the test signals produces the input waveform andthe other test signal is applied to the element under test to producethe output waveform.
 41. The system of claim 29, wherein the distortionmetric is based on compliance with a standard describing a maximumamount of relative noise added by the element and a maximum amount ofdifferential waveform and dispersion penalty associated with theelement.
 42. The system of claim 29, wherein the distortion metric isbased on compliance with a standard describing a maximum amount ofrelative noise added by the element or a maximum differential waveformand dispersion penalty associated with the element.
 43. The system ofclaim 29, wherein: the equalizer includes a decision feedback equalizerhaving a feedforward filter and a feedback filter and a slicer;calculating the distortion metric for the element comprises: measuringan input waveform for the element under test, wherein the input waveformis based on the test signal applied to the element; processing the inputwaveform in software, to simulate propagation of the input waveformthrough the reference receiver; and calculating the distortion metricfor the element based on the simulated propagated output waveform andthe simulated propagated input waveform; and the distortion metric is adifference between (a) SNR for the simulated propagated input waveformand (b) SNR for the simulated propagated output waveform, and the SNRfor the simulated propagated input waveform and the SNR for thesimulated propagated output waveform are measured at an input to theslicer.
 44. The system of claim 29, wherein: the equalizer includes adecision feedback equalizer having a feedback filter and a slicer;calculating the distortion metric for the element comprises: measuringan input waveform for the element under test, wherein the input waveformis based on the test signal applied to the element; processing the inputwaveform in software, to simulate propagation of the input waveformthrough the reference receiver; and calculating the distortion metricfor the element based on the simulated propagated output waveform andthe simulated propagated input waveform; and the distortion metric is adifference between (a) SNR for the simulated propagated input waveformand (b) SNR for the simulated propagated output waveform, and the SNRfor the simulated propagated input waveform and the SNR for thesimulated propagated output waveform are measured at an input to theslicer.
 45. The system of claim 29, wherein: the equalizer includes afeedforward equalizer having a feedforward filter and a slicer;calculating the distortion metric for the element comprises: measuringan input waveform for the element under test, wherein the input waveformis based on the test signal applied to the element; processing the inputwaveform in software, to simulate propagation of the input waveformthrough the reference receiver; and calculating the distortion metricfor the element based on the simulated propagated output waveform andthe simulated propagated input waveform; and the distortion metric is adifference between (a) SNR for the simulated propagated input waveformand (b) SNR for the simulated propagated output waveform, and the SNRfor the simulated propagated input waveform and the SNR for thesimulated propagated output waveform are measured at an input to theslicer.
 46. The system of claim 29, wherein the distortion metricincludes dWDP.
 47. The system of claim 29, wherein the communicationslink comprises a microwave channel.
 48. The system of claim 29, whereinthe communications link comprises a radio frequency channel.
 49. Thesystem of claim 29, wherein the communications link comprises a cablechannel.